J OURNAL OF C RUSTACEAN B IOLOGY, 33(5), 633-640, 2013
FACTORS INFLUENCING THE DISTRIBUTION OF KONA CRABS RANINA RANINA
(BRACHYURA: RANINIDAE) CATCH RATES IN THE MAIN HAWAIIAN ISLANDS
Lennon R. Thomas 1,∗ , Gerard T. DiNardo 2 , Hui-Hua Lee 3 ,
Kevin R. Piner 4 , and Samuel E. Kahng 1
1 Hawaii
Pacific University, 41-202 Kalanianaole Highway, Waimanalo, HI 96795, USA
Fisheries, Pacific Islands Fisheries Science Center, 2570 Dole Street, Honolulu, HI 96822, USA
3 Joint Institute of Marine and Atmospheric Research, 2570 Dole Street, Honolulu, HI 96822, USA
4 NOAA Fisheries, Southwest Fisheries Science Center, 8604 La Jolla Shores Drive, La Jolla, CA, USA
2 NOAA
ABSTRACT
A generalized linear model and commercial catch report data were used to describe spatial and temporal patterns in Kona crab, Ranina
ranina Linnaeus, 1758, catch rates in the Main Hawaiian Islands. Three alternative hypotheses regarding factors influencing the temporal
and spatial distribution of Kona crabs were evaluated using multi-model inference. Broad-scale island effects explain the spatial distribution
of catch rates better than the finer-scale factors of depth and swell exposure. Interdecadal declines in catch rates were noted for islands with
high human density, while other islands had stable or increasing catch rates. The interdecadal changes in catch rates may be explained by
changes in population abundance and management-induced changes in fishing patterns in the recent period. Kona crab behaviors associated
with the reproductive cycle contribute to seasonal variations in observed catch rates.
K EY W ORDS: crab fishery, distribution patterns, generalized linear model, Kona crab, Ranina ranina
DOI: 10.1163/1937240X-00002171
I NTRODUCTION
Kona crabs, Ranina ranina Linnaeus, 1758, are large marine
brachyurans found throughout the tropical and subtropical
Indo-Pacific region in coastal waters. The habitat of Kona
crab is described as sandy substrata from 2 to 200 meters, in
areas subject to strong currents and adjacent to coral reefs
(Vansant, 1978). Kona crabs are opportunistic scavengers
and spend the majority of time buried in the sand to avoid
predators, emerging only to feed and mate (Skinner and Hill,
1986).
The length of time that Kona crabs spend emerged from
the sand, is thought to be closely related to their annual reproductive cycle (Skinner and Hill, 1987). The female Kona
crab reproductive cycle can be divided into 5 stages based
on the gonadosomatic index and histological changes in the
ovary (Minagawa et al., 1993): multiplication, DecemberJanuary; development, February-March; ripe, April-May;
spawning, May-August; and recovery, August-November. In
pre-spawning months female Kona crabs emerge more frequently and respond faster to food (Skinner and Hill, 1987).
During spawning months, they spend significantly longer
periods buried in the sand (Skinner and Hill, 1986; Kennelly
and Watkins, 1994). A similar behavior pattern has been observed in male Kona crabs but on a smaller scale (Skinner
and Hill, 1986).
Identifying the temporal and spatial distributions is essential to understanding the ecology of Kona crabs and,
ultimately, their response to disturbances such as fishing.
∗ Corresponding
Lacking scientifically designed population surveys, statistical analyses can be applied to fishery-dependent data to
standardize effects of changing conditions and fishermen behavior (Hinton and Maunder, 2004), with the advantage of
large sample sizes not usually available in scientific surveys.
Properly standardized, fishery-dependent data can be used to
analyze factors influencing the spatial distribution and abundance of populations (Sullivan and Rebert, 1998; Bigelow
et al., 1999; Campana and Joyce, 2002; Guisan et al., 2002;
Maynou et al., 2003). However, changes in catch rates can
be caused by a number of other factors and may not reflect
changes in stock abundance (Maunder and Punt, 2004). Results of catch rate standardization should be interpreted with
caution and consideration of all potential factors influencing
catch rates (Maunder and Punt, 2004).
Although Kona crabs are widely distributed throughout the Indo-Pacific, most of our knowledge of Kona crab
ecology has been obtained from studies in Australian waters where the largest Kona crab commercial fishery exists (Kennelly and Scandol, 2002; Brown, 2008). To monitor the Kona crab population, Australia has developed a
standardized Kona crab fishing methods to conduct fisheryindependent surveys (Kennelly, 1994; Kennelly and Scandol, 2002). Fishery-independent surveys in Australia show
that Kona crab abundance varies significantly by time period, location and depth (Kennelly, 1994; Kennelly and
Scandol, 2002; Brown et al., 2008).
author; e-mail: [email protected]
© The Crustacean Society, 2013. Published by Brill NV, Leiden
DOI:10.1163/1937240X-00002171
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JOURNAL OF CRUSTACEAN BIOLOGY, VOL. 33, NO. 5, 2013
Comparatively little is known about the biology, ecology and distribution of Kona crabs in other regions. Understanding the biology, ecology and distribution of Kona crabs
is important as their high discard mortality rate (Kennelly
and Watkins, 1990), relatively slow growth rates (Chen and
Kennelly, 1999) and the high value they demand in Hawaii
(Vansant, 1978) make them susceptible to overfishing. The
objective of this study is to identify factors that may be affecting the distribution of Kona crabs in the main Hawaiian Islands (MHI) using fishery-dependent data. Year, season and three hypotheses of factors potentially influencing
the spatial distribution in the MHI were tested, along with
an evaluation of temporal patterns in effort and catch rate.
M ATERIALS AND M ETHODS
Study Area
The MHI are located between 19° and 22°N and 155° and 160°W along
the 500 km southeastern-most portion of the Hawaiian Archipelago, the
world’s most isolated seamount chain (Fig. 1). From north to south, four
major platforms exist in the MHI in the following order: Kauai (includes
Ni’ihau and Ka’ula Rock), Oahu, Maui Nui (includes Molokai, Lanai and
Kaho’olawe) and Hawai’i. The direction of swell exposure around the MHI
determines the level of wave intensity, as areas exposed to North Pacific
swells experience the greatest wave intensity followed by areas exposed to
northeast trade swell, and southern swell (Fletcher et al., 2008). The Hawaii
Division of Aquatic Resources (HDAR) inshore fishing area boundary
occurs on average 2.61 km from shore and along the 100 ftm contour line
(Smith, 1993). The HDAR inshore fishing area boundary was used as a
proxy for depth and Kona crab habitat.
Data Source
Commercial Kona crab catch report data for tangle nets were obtained from
the State of Hawaii, Division of Aquatic Resources (HDAR) for 19482009. The catch report data included the date, area fished, the fisher license
number, and the landed weight (kg) of Kona crabs. To meet the HDAR
confidentiality requirements, data were aggregated to at least three fishers
per unit of time and space.
A fishing trip was defined as a catch report entry with a unique date
and fishermen license number. Catch rate was defined as landings (kg)
of Kona crab per trip (kg trip−1 ). Fishing methods such as the design
of the tangle nets, the soak time, and the number of nets used varies by
fisher and can have a significant impact on catch rates (Kennelly, 1989;
Kennelly and Craig, 1989). However, all fishing trips were assumed equal
because details of fishing effort for individual trips were not available.
Interviews with Hawaii Kona crab fishermen indicated that fishing effort
is relatively consistent among fishermen. Hawaii fishermen have found that
fishing effort for tangle nets is highly related to the soaking time, which is
generally short, and constant per trip, to avoid predators and damage of the
gear.
Statistical Analyses
To characterize temporal and spatial distributions of Kona crabs, average
catch rate (kg trip−1 ) and total effort (no. of trips) were calculated and
incorporated into a GIS program to create a geographical representation.
Catch report data were further divided into three time periods to account
for regulatory changes affecting catchabilty that could not be accounted for
in the statistical analysis (Arregun-Sanchez, 1996): 1948-1998, 1998-2006
and 2006-2009. In 1998, bottomfishers were prohibited from participating
in the Kona crab fishery, and in 2006 the taking of female crabs was
prohibited. Therefore, data for the three time periods were analyzed
separately, assuming that catchability is constant in each time period.
Generalized linear models (GLMs; Nelder and Wedderburn, 1972) were
used to investigate spatial and temporal factors expected to explain observed
variations in Kona crab catch rate. Analyses were performed using the GLM
procedure in SAS software (SAS Institute, 1990), and assuming a normal
error distribution. Prior to model fitting, the data were log transformed. All
models were evaluated for compliance with the statistical assumptions.
Year, season, and three area hypotheses were considered for inclusion
in the model as explanatory variables. Year was considered because Kona
crab catch rate was expected to vary significantly over the 63 years of
data. Season was considered because the vulnerability of crabs to fishing
gear was expected to change seasonally with changes in the reproductive
cycle. Five seasons were defined for the model on the basis of the 5 stages
of oogenesis experienced by female Kona crabs (Minagawa et al., 1993).
Three alternative spatial hypotheses were considered regarding how area
may influence Kona crab distribution: (1) island platform (Hawaii, Maui
Nui, Oahu, Kauai), (2) depth (inside or outside of the HDAR inshore fishing
area boundary) and (3) swell exposure (north, trade, south, or sheltered from
swell) (Fletcher et al., 2008) (Fig. 1).
Explanatory variables were included in the model using a stepwise
model selection. Akaike’s Information Criterion (AIC) was used for model
selection, as well as to evaluate the alternative area hypotheses (Burnham
and Anderson, 2002). The log-transformed catch rate was estimated as the
least-squares mean of the factors selected based on the best-fit model and
then back-transformed to derive the median standardized catch rate. Tukey’s
post hoc tests were then used to identify significant differences between
factor levels.
Fig. 1. The main Hawaiian Islands (MHI) showing primary swell exposures of each fishing area, the 200-m contour line (white dotted line), and the break
between the four major island platforms (black dashed line).
THOMAS ET AL.: RANINA RANINA CATCH RATES IN THE MAIN HAWAII
R ESULTS
Spatial distribution patterns (Fig. 2) indicate the highest
catch rates of Kona crab and the highest fishing effort
have consistently been found at Penguin Bank, which is
an inshore area off the southwest coast of Maui Nui island
platform experiencing primarily southern swell. High catch
rates of Kona crabs were also observed inshore and offshore
of the island of Niihau (Kauai island platform). Interdecadal
patterns indicate strong changes in catch rates that differ by
island platform (Figs. 2 and 3).
The best model based on model selection criteria included
the factors year, season, and island platform explaining
28%, 29% and 52% of the variation in catch rate for the
three time periods, respectively (Tables 1 and 2). Island
platform provided the best explanation of the distribution of
Kona crab catch rate. However the alternate hypotheses of
swell exposure and to a lesser extent depth also explained a
significant amount of the variability in observed catch rate
(Table 1). The island platform factor was significant for all
three time periods in the final models, while the factors
of season and year were significant for the 1948-1998 and
1998-2006 time periods (Table 1).
Catch rates of Kona crabs varied significantly between all
island platforms (Fig. 3). Based on Tukey’s post-hoc tests,
Maui Nui showed significantly (p < 0.001) higher Kona
crab catch rates from 1948 to 1998, followed by Kauai,
Oahu, and Hawai’i, showing the lowest Kona crab catch
rate. From 1998 to 2006, Maui Nui showed significantly
(p < 0.001) higher Kona crab catch rate, followed by Kauai,
Hawai’i, and Oahu with the lowest. For the 2006 to 2009
time series, Kauai showed significantly (p < 0.001) higher
Kona crab catch rate than all other island platforms, followed
by Maui Nui, Hawai’i, and Oahu with the lowest.
Estimated catch rates for Kona crab catch rate varied
significantly by season and year during 1948-1998 and
1998-2006 (Table 1). Significantly (p < 0.001) higher
Kona crab catch rates were observed during the MayAugust season and the March-April season from 1948 to
1998 (Fig. 4). However, during 1998-2006, the significantly
higher catch rates (p < 0.001) were observed during
the March-April season. From 2006 to 2009, there was
no catch reported during the May-August season and no
significant differences in Kona crab catch rates by year
or season were observed. An interdecadal decline in Kona
crab catch rate was noted for Oahu but not for other island
platforms (Figs. 2a and 3). Fishing effort remained relatively
stable across island platfoms, with absolute levels of effort
declining for some island platforms (Fig. 2b).
D ISCUSSION
Broad spatial-scale effects (island platform) best explained
the variation in Kona crab catch rates in the MHI. Assuming that catch rates are proportional to population abundance
(Maunder and Punt, 2004), the spatial differences in abundance between island platforms may be influenced by local
habitat availability, and temporal changes within island platform abundance by habitat degradation and fishing due to
proximity to high human density. Oahu, which has the highest densities of human residents in the MHI, also has the
lowest catch rate of Kona crabs and a strong interdecadal
635
negative trend in catch rate. Similar negative relationships
between the abundance of large coral reef fish species and
human proximity have been noted in Hawaii (Friedlander
and DeMartini, 2002; Williams et al., 2008) and in other island systems (DeMartini et al., 2008; Richards et al., 2012).
Within island platform, finer spatial-scale effects of swell
exposure and to a lesser extent depth influence the catch rate
of Kona crab. At the Maui Nui Island platform, higher catch
rates of Kona crabs were observed in the areas exposed to
southern swell. Areas exposed to southern swell experience
the least wave intensity (aside from sheltered areas) and are
relatively calm when compared to areas exposed to north or
trade swell (Fletcher et al., 2008). This result was similar
to that reported in Australia, where large swell activity was
negatively correlated to Kona crab landings (Brown et al.,
2008). Shallow areas exposed to southern swell are also
ideal conditions for the accumulation of thick layers of sand
(Hampton et al., 2003), which are preferred habitat for Kona
crab. Shallow-water benthic habitat mapping has revealed
that the island platform of Maui Nui has the largest area of
sandy benthic habitat available (Battista et al., 2007).
Although Kona crab catch rates appear negatively correlated to large swell activity, hydrography may influence
the effect of swell intensity. High catch rates of Kona crabs
were observed on the Kauai island platform in areas that
were exposed to the high wave intensity of North Pacific
swell. Large swell is thought to impact the ability of the
crab to detect the location of the bait and may also impair
a crab’s ability to emerge from the sand and move on the sea
floor (Brown et al., 2008). However, the rotational movement of the water column that is caused by the large swell
decreases with depth (Brown et al., 2008). Deeper waters occur relatively close to shore around the Kauai island platform
(Smith, 1993) and may offer crabs refuge from the strong
wave intensity.
Depth appears the least important of our hypotheses
explaining Kona crab distribution. The reduced importance
of depth on catch rate may be due to the coarseness of the
depth data used. Fishing locations were reported statistical
areas that included a range of depths which required a gross
summarization of the depth of catch in this work. Despite
the coarseness of the data, it is notable that the Maui Nui
island platform has the widest insular shelf and contains
more benthic area in the suitable depth range (<200 m)
than all other island platforms combined (Brown, 1985). The
largest extension of the insular shelf extends over 50 km
and occurs off the southwest coast of Molokai (Maui Nui
island platform), creating the fishing area known as Penguin
Bank (Smith, 1993). The highest catch rates of Kona crabs
have consistently been observed at Penguin Bank, which is
described as having large, flat sandy fields (Moffitt et al.,
1989). The Kauai island platform contains the second largest
area in a suitable depth range for Kona crabs followed by
Oahu and Big Island. This pattern of available area in a
Kona crab suitable depth range corresponds to the observed
pattern of Kona crab catch rates for the majority of the data,
suggesting that an appropriate depth range is an important
component of Kona crab habitat.
As with swell intensity, the impact of depth on catch rate
may be influenced by hydrography. The Maui Nui and Kauai
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JOURNAL OF CRUSTACEAN BIOLOGY, VOL. 33, NO. 5, 2013
Fig. 2. Relative Kona crab, Ranina ranina, (a) catch rate (kg trip−1 ) and (b) effort by statistical fishing area in the main Hawaii Islands (MHI) based on the
following time periods: 1948-1972, 1973-1990 and 1991-2009. Data were not reported for statistical fishing areas with less than 3 reporting fishers.
637
THOMAS ET AL.: RANINA RANINA CATCH RATES IN THE MAIN HAWAII
Fig. 3. Standardized Kona crab, Ranina ranina, catch rate (kg trip−1 ) by island platform from the following time periods: 1948-1998, 1998-2006 and
2006-2009. Island platforms included Hawaii, Maui Nui, Oahu, and Kauai. The horizontal line shows the median standardized Kona crab catch rate for each
season. The bottom and top of the box show the 25th and 75th percentiles, respectively. The dashed vertical lines indicate the minimum and the maximum
values.
Table 1. Akaike’s Information Criterion (AIC) results for each of the generalized linear models that were fit to Kona crab, Ranina ranina, commercial
catch report data. Each model was run with data from the following time periods: 1948-1998, 1998-2006 and 2006-2009. AIC values were used for model
selection, the lowest AIC value representing the best-fit model. The chosen model included the factors year, season, and island platform. Significance of
each added model factor are indicated by asterisks (∗∗ p < 0.0001 and ∗ p < 0.05).
Model
AIC value
Intercept
Year
Year, season
Year, season, island platform
Year, season, depth
Year, season, swell exposure
1948-1998
1998-2006
2006-2009
27313.64
26236.25∗∗
26206.27∗∗
24120.46∗∗
26045.45∗∗
25378.56∗∗
4468.60
4432.44∗∗
4410.75∗∗
3964.34∗∗
4408.06∗
4108.43∗
2005.84
2006.48
2003.95∗
1511.53∗∗
2005.52
1841.56∗∗
Table 2. Analysis of variance table for the best-fit generalized linear models (GLMs) including year, season, and island platform as explanatory variables.
The GLM was fit to Kona crab (Ranina ranina) commercial catch report data for data from the following time periods: 1948-1998, 1998-2006 and 2006-2009.
Time period
n
Residual df
Deviance
Adjusted R 2
F -value
p>F
1948-1998
1998-2006
2006-2009
9892
1564
695
9834
1548
685
6555.48
1130.18
346.97
0.28
0.29
0.52
771.93
173.09
239.45
<0.0001
<0.0001
<0.0001
638
JOURNAL OF CRUSTACEAN BIOLOGY, VOL. 33, NO. 5, 2013
Fig. 4. Standardized Kona crab, Ranina ranina, catch rate (kg trip−1 ) by season from the following time periods: 1948-1998, 1998-2006 and 2006-2009.
The 5 seasons based on the 5 reproductive stages of female Kona crab were: September-October (1), November-December (2), January-February (3), MarchApril (4) and May-August (5). The horizontal line shows the median standardized Kona crab catch rate for each season. The bottom and top of the box show
the 25th and 75th percentiles, respectively. The dashed vertical lines indicate the minimum and the maximum values.
island platforms share similar hydrography and this may be
a contributing factor to the high catch rates of Kona crabs
in these regions. Two of the most commercially productive
areas are Penguin Bank (Maui Nui platform) and Niihau
(Kauai platform) (Onizuka, 1972; Smith, 1993). While Penguin Bank and areas off of Niihau experience dramatically
different swell exposures, they are similar in that they include relatively shallow banks (<200 m) that drop abruptly
to oceanic depths (>500 m) along the banks’ edge (Moffitt
et al., 1989; Smith, 1993). Increased rates of productivity
are expected to occur at these banks, as deep, nutrient-rich
currents are deflected upwards upon encountering the relatively shallow edges of the bank (Haight et al., 1993). In
Australia, benthic velocity rates have been positively correlated to Kona crab catch rates (Craig and Kennelly, 1991).
Higher catch rates of plankton are found in these regions
(Haight et al., 1993), providing ideal feeding conditions for
the survival and development of Kona crab zoea (Minagawa
and Murano, 1993). Higher production rates will also result
in a higher concentration of detritus material available for
the opportunistic adult Kona crabs.
The significant seasonal pattern in MHI Kona crab catch
rate is consistent with the expected behavioral patterns of fe-
males and supports previous studies which found Kona crab
behavior is closely associated with their reproductive cycle
(Skinner and Hill, 1986; Skinner and Hill, 1987; Kennelly,
1992; Kennelly and Watkins, 1994). The spawning season
for Kona crabs is from May to August, in the MHI, with
highest frequency of ovigerous females occurring in June
and July (Fielding and Haley, 1976). During the 1948-1998
period, the highest catch rate of Kona crabs was observed
in the May-August season. During this period, the majority
of catch was taken in May when females are expected to be
pre-ovigerous and more active foragers (Skinner and Hill,
1987). Pre-ovigerous females have responded significantly
faster to food stimuli in previous studies (Skinner and Hill,
1987), which may make them more vulnerable to fishing.
The interdecadal decline in catch rate of Kona crab
around Oahu may be attributed to a combination of habitat
changes, fishing and changes in fishing patterns. Post-1998
seasonal management measures reduced catch of Kona
crab during May. Because females remained buried in the
sand while ovigerous, shifting fishing activity to the period
of females peak ovigerous months likely resulted in the
lower observed catch rates after 1998. The declining trend
in catch rate from 1998 to 2006 could also have been
THOMAS ET AL.: RANINA RANINA CATCH RATES IN THE MAIN HAWAII
influenced by a change in fishermen composition. During
this time period, bottomfishers were restricted from taking
Kona crabs. Bottomfishers typically target deep, offshore
areas and will simultaneously soak Kona crabs nets and
bottomfish. The observed decline in catch rate may have
been a result of the removal of bottomfishers who may have
known the most productive ground for Kona crab. After
2006, catch was restricted to male crabs only. This not
only resulted in a lower observed catch rate but explains
the reduced importance of season in the model if seasonal
variation in catch rate is a result of changing female behavior
and its correlation to the reproductive cycle (Skinner and
Hill, 1987).
Despite the difficulties associated with using fisherydependent data, our results suggest that the spatial distribution of Kona crab catch rate in Hawaii is likely influenced by
the bathymetry, oceanographic conditions, and habitat available at each island platform. Seasonal fluctuations in catch
rate are likely caused by variations in Kona crab behavior associated with the reproductive cycle. While spatial and temporal variations in catch rates are related to differences in
population abundance, other factors influencing catch rate
including local weather conditions, crab behavior, and fishermen behavior should be recognized (Arreguin-Sanchez,
1996; Maunder and Punt, 2004). Improperly standardized
changes in fishermen behavior can invalidate the assumption of proportionality between catch rate and abundance
(Harley et al., 2001). Future fishery-independent investigations would greatly contribute to the knowledge of this fishery, and could be used to explore smaller-scale features that
might be potentially influencing the spatial distribution of
Kona crabs.
ACKNOWLEDGEMENTS
Funding for this project was provided by the NOAA Western Pacific Regional Fishery Management Council through the NOAA Coral Reef Conservation Grant Program, award number NA09NMF441038. The authors
wish to thank Reginald Kokoburn, Wendy Seki and the rest of the State of
Hawaii, Division of Aquatic Resources staff for their assistance in obtaining and understanding the commercial catch reports. The authors also wish
to thank Jordan Watson, David Hyrenbach, Eric Vetter, Mark Mitsusasyu,
Josh DeMello, Marlowe Sabater and Paul Dalzell for their support and contributions to this project.
R EFERENCES
Arreguin-Sanchez, F. 1996. Catchabililty: a key parameter for fish stock
assessment. Reviews in Fish Biology and Fisheries 6: 221-242.
Battista, T. A., B. M. Costa, and S. M. Anderson. 2007. Shallow-Water
Benthic Habitats of the Main Eight Hawaiian Islands (DVD). NOAA
Technical Memorandum NOS NCCOS 61, Biogeography Branch, Silver
Spring, MD.
Bigelow, K. A., C. H. Boggs, and X. He. 1999. Environmental effects on
swordfish and blue shark catch rates in the US north Pacific longline
fishery. Fisheries Oceanography 8: 178-198.
Brown, I. W. 1985. The Hawaiian Kona crab fishery: report on a visit
to Honolulu in January 1983. Fishing Industry project QS 85005 –
Final report. Queensland Department of Primary Industries and Fisheries,
Brisbane, QLD.
, J. Scandol, D. Mayer, M. Campbell, S. Kondyias, M. McLennan,
A. Williams, K. Krusic-Golub, and T. Treloar. 2008. Reducing uncertainty in the assessment of the Australian spanner crab fishery. Fishing
Industry project PR07-3314 – Final report. Queensland Department of
Primary Industries and Fisheries, Brisbane, QLD.
Burnham, K. P., and D. R. Anderson. 2002. Model Selection and Multimodel Inference. 2nd Edition. Springer, New York, NY.
639
Campana, S. E., and W. N. Joyce. 2004. Temperature and depth associations
for porbeagle shark (Lamna nasus) in the northwest Atlantic. Fisheries
Oceanography 13: 52-64.
Craig, J. R., and S. J. Kennelly. 1991. An inexpensive instrument for
measuring benthic current velocity and direction at sea. Estuarine,
Coastal and Shelf Science 32: 633-638.
DeMartini, E. E., A. M. Friedlander, S. A. Sandin, and E. Sala. 2008.
Differences in fish-assemblage structure between fished and unfished
atolls in the northern Line Islands, central Pacific. Marine Ecology
Progress Series 356: 199-215.
Fielding, A., and S. R. Haley. 1976. Sex ratio, size at reproductive maturity,
and reproduction of the Hawaii Kona crab, Ranina ranina Linnaeus
(Brachyura, Gymnopleura, Raninidae). Pacific Science 30: 131-145.
Fletcher, C. H., C. Bochicchio, C. L. Conger, M. Engels, E. J. Feierstein,
L. N. Frazer, C. R. Glenn, R. W. Grigg, E. E. Grossman, J. N. Harney,
E. Isoun, C. V. Murray-Wallace, J. J. Rooney, K. Rubin, C. E. Sherman,
and S. Vitousek. 2008. Geology of Hawaii Reefs. Coral Reefs of the
USA. Springer-Science + Business Media, Dania Beach, FL.
Friedlander, A. M., and E. E. DeMartini. 2002. Contrasts in catch rate,
size, and biomass of reef fish between the northwestern and the main
Hawaiian Islands: the effects of fishing down apex predators. Marine
Ecology Progress Series 230: 253-264.
Guisan, A., T. C. Edwards, and T. Hastie. 2002. Generalized linear and
generalized additive models in studies of species distribution: setting the
scene. Ecological Modelling 157: 89-100.
Haight, W. R., J. D. Parrish, and T. A. Hayes. 1993. Feeding ecology of the
deepwater Lutjanid Snappers at Penguin Bank, Hawaii. Transactions of
the American Fisheries Society 122: 328-347.
Hampton, M. A., C. T. Blay, C. Murray, L. Z. Torresan, C. Z. Frazee, B. M.
Richmond, and C. H. Fletcher. 2003. Data Report: geology of reef-front
carbonate sediment deposits around Oahu, Hawaii. US Department of the
Interior, US Geological Survey, Reston, VA.
Harley, S. J., R. A. Myers, and A. Dunn. 2001. Is catch-per-unit-effort
proportional to abundance? Canadian Journal of Fisheries and Aquatic
Sciences 58: 1760-1772.
Hinton, M. J., and M. N. Maunder. 2004. Methods for standardizing CPUE
and how to select among them. Collective Volume of Scientific Papers
ICCAT 56: 169-177.
Kennelly, S. J. 1989. Effects of soak-time and spatial heterogeneity on
sampling populations of spanner crabs Ranina ranina. Marine Ecology
Progress Series 55: 141-147.
. 1992. Distribution, abundances and current staus of exploited
populations of spanner crabs Ranina ranina off the east coast of
Australia. Marine Ecology Progress Series 85: 227-235.
, and J. R. Craig. 1989. Effects of trap design, independence of traps
and bait on sampling populations of spanner crabs Ranina ranina. Marine
Ecology Progress Series 51: 49-56.
, and J. P. Scandol. 2002. Using a fishery-independent survey to
assess the status of a spanner crab Ranina ranina fishery: univariate
analyses and biomass modeling. Crustaceana 1: 13-39.
, and D. Watkins. 1994. Fecundity and reproductive period, and their
relationship to catch rates of spanner crabs, Ranina ranina, off the east
coast of Australia. Journal of Crustacean Biology 14: 146-150.
,
, and J. R. Craig. 1990. Mortality of discarded spanner
crabs Ranina ranina (Linnaeus) in a tangle-net fishery-laboratory and
field experiments. Journal of Experimental Marine Biology and Ecology
140: 39-48.
Linnaeus, C. 1758. Systema Natura eper Regna tria naturae secundum
Classes, Ordinus, Genera, Species cum Characteribus, Diferentis Synonymis. Locis 10th Edition. Vol. 1. Salvii, Holmiae.
Maunder, M. N., and A. E. Punt. 2004. Standardizing catch and effort data:
a review of recent approaches. Fisheries Research 70: 141-159.
Maynou, F., M. Demestre, and P. Sanchez. 2003. Analysis of catch per unit
effort by multivariate analysis and generalised linear models for deepwater crustacean fisheries off Barcelona (NW Mediterranean). Fisheries
Research 65: 257-269.
Minagawa, M., J. R. Chiu, M. Kudo, F. Ito, and F. Takashima. 1993.
Female reproductive biology and oocyte development of the red frog
crab, Ranina ranina, off Hachijojima, Izu Islands, Japan. Marine Biology
115: 613-623.
, and M. Murano. 1993. Larval feeding rhythms and food consumption by the red frog crab Ranina ranina (Decapoda, Raninidae) under
laboratory conditions. Aquaculture 113: 251-260.
640
JOURNAL OF CRUSTACEAN BIOLOGY, VOL. 33, NO. 5, 2013
Moffitt, R. B., F. A. Parrish, and J. J. Polovina. 1989. Community structure,
biomass and productivity of deepwater artificial reefs in Hawaii. Bulletin
of Marine Science 44: 616-630.
Nelder, J. A., and R. M. Wedderburn. 1972. Generalized linear models.
Journal of the Royal Statistical Society 135: 370-384.
Onizuka, E. W. 1972. Management and development investigations of
the Kona crab, Ranina ranina (Linnaeus). Division of Fish and Game,
Department of Land and Natural Resources Report, Honolulu, Hawaii.
Richards, B. L., I. D. Williams, O. J. Vetter, and G. J. Williams. 2012.
Environmental factors affecting large-bodied coral reef fish assemblages
in Mariana Archipelago. PLoS One 7: e31374.
Skinner, D. G., and B. J. Hill. 1986. Catch rate and emergence of male and
female spanner crabs (Ranina ranina) in Australia. Marine Biology 91:
461-465.
, and
. 1987. Feeding and reproductive behavior and their
effect on catchability of the spanner crab Ranina ranina. Marine Biology
94: 211-218.
Smith, K. S. 1993. An ecological perspective on inshore fisheries in the
Main Hawaiian Islands. Marine Fisheries Review 55: 34-49.
Sullivan, P. J., and S. D. Rebert. 1998. Interpreting Pacific halibut catch
statistics in the British Columbia individual quota program. Canadian
Journal of Fisheries and Aquatic Sciences 55: 99-115.
Vansant, J. P. 1978. A survey of the Hawaiian Kona crab fishery. Thesis for
the degree of Master of Science, Oceanography, University of Hawaii:
1-59.
Williams, I. D., W. J. Walsh, R. E. Schroeder, A. M. Friedlander, B. L.
Richards, and K. A. Stamouolis. 2008. Assessing the importance of
fishing impacts on Hawaiian coral reef fish assemblages along regionalscale human population gradients. Environmental Conservation 35: 261272.
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AVAILABLE ONLINE: 27 May 2013.